Not provided
Not provided
Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| 49800 | Other Identifier | Stanford IRB |
Not provided
Not provided
Not provided
Difficulty enrolling due to COVID closures
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Atrial fibrillation is a serious public health issue that affects over 5 million Americans in whom it may cause skipped beats, dizziness, stroke and even death. This study seeks to improve our understanding of the causes of atrial fibrillation and to design new and more effective therapy for this heart rhythm disorder.
This project will focus on the development of a novel paradigm for electrophysiologic data analysis and interpretation using cloud-based computing resources and mobile technology. Currently, electrophysiologic data gathered during a procedure is analyzed by the operator using multiple separate desk-based computer systems in the electrophysiology laboratory. The investigators propose that advances in cloud-based computing resources and network connectivity should apply a mobile paradigm to apply to invasive electrophysiologic procedures.
This project will provide proof-of-concept that open-access software the investigators have developed and made available online could be used, via a mobile phone interface, to identify sites in the heart where therapy is effective. At no time will patient therapy be guided by this system. The investigators will pursue therapy using only clinical means. In parallel, a double-blinded team will analyze data in real time using our online software visualized on a smartphone. Only when the case is concluded will the data be unblinded, to determine if the mobile system was accurate in real time.
Thus, development and testing of the cloud-based computing system is designed only to establish feasibility of the paradigm, followed by improvement of computational modeling algorithms. The data that is collected will add to the investigators' existing unique catalogue of multimodal (structural, clinical, and electrophysiologic) data.
The importance of this novel paradigm is to move from analyzing large volumes of data in isolation to creating a mobile platform, and to allow scalability to increase access, such as to underdeveloped medical centers.
Not provided
Not provided
Not provided
Not provided
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Mapping Accuracy | Location of driver regions for AF | During Procedure (Electrophysiology Study and Ablation) |
| Termination of atrial fibrillation | Does ablation at any driver region lead to AF termination | During Procedure (Electrophysiology Study and Ablation) |
Not provided
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Subjects will be men and women of any ethnicity aged 21-80 years undergoing ablation at Stanford of AF. Patients will have failed or be intolerant of ≥ 1 anti-arrhythmic drug or not willing to accept antiarrhythmic drug therapy. 50 patients will be enrolled at Stanford University over 1-2 years.
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Sanjiv Narayan, MD, PhD | Stanford University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Stanford University | Stanford | California | 94305 | United States |
Not provided
| ID | Term |
|---|---|
| D001281 | Atrial Fibrillation |
| D001145 | Arrhythmias, Cardiac |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
Not provided
Not provided
Not provided
Not provided
Not provided